Signal source recommendation method and related device

Abstract

The implementation mode of the present application provides a method for recommending a number source and related devices. The number source recommendation method includes: generating a medical demand portrait based on the medical-related behavior data generated by the user account; wherein the medical demand portrait is used to characterize the disease information of the user account; identifying matching doctor information that matches the medical demand portrait from a doctor information database based on the medical demand portrait; wherein the doctor represented by the matching doctor information is good at treating the disease represented by the disease information; monitoring the number source corresponding to the matching doctor information, and sending the user account with the available registration source recommendation information corresponding to the target doctor information when there is an available registration source corresponding to the target doctor information screened out from the matching doctor information. The number source recommendation method and related devices can reduce the waiting time for a number source.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of computer technology, and in particular, to a number source recommendation method and related devices. Background Art

[0002] Online medical platforms can provide users with more convenient online registration services than offline registration. Users can make appointments in advance through the online medical platform and go to the hospital for treatment at the agreed time, saving time queuing and waiting for registration offline.

[0003] Specifically, users can log in to the online medical platform and enter the registration system. They can search for the corresponding department through the search function or classification list to trigger the system to automatically display the available appointment numbers of each doctor in the department. Users can make appointments for designated times for their intended doctors according to their own needs.

[0004] However, when appointment numbers are in short supply, users usually can only wait until a number becomes available before making an online appointment, which results in a long waiting time for an appointment. Summary of the invention

[0005] In view of this, multiple embodiments of the present application are dedicated to providing a number source recommendation method and related devices, which can reduce the waiting time for the number source.

[0006] One embodiment of the present application provides a method for recommending appointment sources, including: generating a medical need portrait based on medical-related behavior data generated by a user account; wherein the medical need portrait is used to represent the disease information of the user account; identifying matching doctor information that matches the medical need portrait from a doctor information database based on the medical need portrait; wherein the doctor represented by the matching doctor information is good at treating the disease represented by the disease information; monitoring the appointment sources corresponding to the matching doctor information, and sending appointment source recommendation information corresponding to the target doctor information to the user account when there is an available appointment source corresponding to the target doctor information screened out from the matching doctor information.

[0007] One embodiment of the present application provides a method for displaying appointment source recommendation information, including: receiving the appointment source recommendation information corresponding to the target doctor information sent by the appointment source recommendation method; and displaying the appointment source recommendation information.

[0008] One embodiment of the present application provides a device for recommending a number source, including: a medical need portrait generation module, used to generate a medical need portrait based on medical-related behavior data generated by a user account; wherein the medical need portrait is used to represent the disease information of the user account; a doctor information matching module, used to identify matching doctor information that matches the medical need portrait from a doctor information database based on the medical need portrait; wherein the doctor represented by the matching doctor information is good at treating the disease represented by the disease information; and a number source recommendation module, used to monitor the number source corresponding to the matching doctor information, and when the target doctor information screened out from the matching doctor information corresponds to an available number source, send the available number source recommendation information corresponding to the target doctor information to the user account.

[0009] One embodiment of the present application provides a device for displaying appointment source recommendation information, including: an information receiving module for receiving the appointment source recommendation information corresponding to the target doctor information sent by the appointment source recommendation device; an information display module for displaying the appointment source recommendation information.

[0010] One embodiment of the present application provides a computer device, which includes a memory and a processor, wherein the memory stores at least one computer program, and the at least one computer program is loaded and executed by the processor to implement the aforementioned number source recommendation method or number source recommendation information display method.

[0011] One embodiment of the present application provides a computer-readable storage medium, in which at least one computer program is stored. When the at least one computer program is executed by a processor, it can implement the aforementioned number source recommendation method or number source recommendation information display method.

[0012] One embodiment of the present application provides a computer program product, which is used to implement the aforementioned number source recommendation method or number source recommendation information display method.

[0013] In multiple implementations provided in the present application, a corresponding medical need portrait is generated based on the medical-related behavior data of the user account. Since the medical need portrait can represent the disease information of the user account, matching doctor information can be identified based on the medical need portrait. The doctor represented by the matching doctor information is good at treating the disease represented by the disease information. Furthermore, when it is monitored that the target doctor information in the matching doctor information corresponds to an available registration source, the corresponding available registration source recommendation information can be recommended to the user account, so as to reduce the waiting time for the appointment source and help the user's appointment needs to be met in a timely manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1A schematic diagram of the interaction between a number source recommendation device and a client provided for one embodiment of the present application.

[0015] Figure 2 A schematic diagram of an application scenario of a method for recommending a number source provided in another embodiment of the present application.

[0016] Figure 3 A flowchart of a method for recommending a number source is provided for one embodiment of the present application.

[0017] Figure 4 A flowchart of a method for displaying number source recommendation information provided in accordance with one embodiment of the present application.

[0018] Figure 5 A schematic diagram of a module of a number source recommendation device provided for one embodiment of the present application.

[0019] Figure 6 A module diagram of a number source recommendation information display device provided for one embodiment of the present application.

[0020] Figure 7 A schematic diagram of a computer device provided for one embodiment of the present application. DETAILED DESCRIPTION

[0021] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments.

[0022] In the description of the embodiments of the present application, it should be understood that the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of the present application, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0023] In related technologies, in order to provide online services to users, online medical platforms usually connect with hospitals, medical institutions and health management systems to provide one-stop medical services, such as registration, consultation, and examination appointments.

[0024] The online appointment service can help users efficiently make appointments when there are available appointments online. Users usually choose doctors / departments based on their health conditions, specific needs, and personal preferences. Due to the limited number of available appointments, sometimes there are no appointments available. Especially for some popular doctors, the available appointments are more limited, and it is difficult to successfully complete online appointments.

[0025] In the above situation, it is usually necessary to wait for the next number release. However, the number-making behavior is random, and users need to frequently check the required number source in order to register in time after the number is released. However, this leads to a long waiting time. In addition, although some online medical platforms provide a number release reminder service, users may not necessarily subscribe to the number release reminder service. Even if users subscribe to the number release reminder service, they still need to wait until the next number is released to receive the reminder information triggered by the number release reminder service. It can be seen that this method still has the problem of a long waiting time.

[0026] Therefore, it is necessary to provide a method for recommending appointment sources, which generates a corresponding medical demand portrait based on the medical-related behavior data of the user account. Since the medical demand portrait can represent the disease information of the user account, the matching doctor information can be identified based on the medical demand portrait. The doctor represented by the matching doctor information is good at treating the disease represented by the disease information. Furthermore, when it is monitored that the target doctor information in the matching doctor information corresponds to an available appointment source, the corresponding available appointment source recommendation information can be recommended to the user account, so as to reduce the waiting time for appointments and help the user's appointment needs to be met in a timely manner.

[0027] See also Figure 1 In the multiple implementations provided in the present application, the number source recommendation method can be applied to an electronic device with certain computing power and network access capability. The electronic device can be a desktop computer, a laptop computer, a tablet computer, or a server. The electronic device can be connected to a client through a network.

[0028] Specifically, the electronic device includes a processor, a memory, a display module, and a network access module for network communication. The processor is used to generate a medical demand portrait based on the medical-related behavior data generated by the user account, identify matching doctor information that matches the medical demand portrait from the doctor information database according to the medical demand portrait, and monitor the number source corresponding to the matching doctor information. The memory is used to store various intermediate data generated in the process of medical-related behavior data, medical demand portraits, matching doctor information, and number source recommendation. The display module is used to display one or more data stored in the memory when a trigger display operation is detected. The network access module is used to send the available registration source recommendation information corresponding to the target doctor information to the client corresponding to the user account when the target doctor information filtered out from the matching doctor information corresponds to the available registration source.

[0029] See also Figure 2. One embodiment of the present application provides an application scenario example of a number source recommendation method. The number source recommendation method may include a client and a server. A user can use the client to log in to the registration platform and use the number source recommendation function provided by the registration platform. In this scenario example, the client is a registration application on a user terminal device, and the server is a background data processing system of the registration platform.

[0030] User A recently had repeated coughing, so he opened the client of the registration platform, searched for the keyword "respiratory department" many times, and visited the detailed introduction page of a respiratory expert doctor in a tertiary hospital, but failed to register successfully many times. These operations of user A can be identified as medical-related behavior data, such as searching keywords, visiting doctor interface records, visiting department list data, and unsuccessful registration records. The user behavior data collection module in the registration platform server is used to collect and structure medical-related behavior data in real time.

[0031] After the server obtains the medical-related behavior data of user A, it generates a medical demand portrait of A based on the medical-related behavior data. For example, the server can use a large language model to conduct an in-depth analysis of user A's search keywords and browsing trajectory, and obtain the following medical demand portrait dimensions: potential health problems: suspected chronic cough or asthma; preferred department: respiratory medicine; preferred hospital: a Class III hospital of interest; preferred doctor: a respiratory specialist doctor who has been visited multiple times.

[0032] Based on the medical needs profile of user A, the server's real-time matching module matches the target doctor information from the server's doctor data collection and processing module. The doctor information is manually reviewed and processed by a large language model in advance to generate data such as each doctor's specialty disease information, department, and hospital. In addition, the server calculates the similarity between doctors based on the similarity evaluation dimension (including specialty disease information, department, region, and hospital). The similarity between doctors is used to determine the matching degree between the matching doctor information and the medical needs profile.

[0033] When the server monitors the dynamic changes in the number source of the target doctor information contained in the doctor information in the real-time doctor number source collection system - for example, a respiratory specialist suddenly releases the available number for the afternoon, the server further analyzes the medical-related behavior data of user A according to the specified filtering rules. For example: user A has visited the doctor's interface, but there was no number available at that time; within the first preset time (for example, within 7 days), A did not successfully register with a department similar to the doctor without a number source who had been visited; within the second preset time (for example, within 3 days), the number of times A visited the page of the doctor without a number source reached the preset threshold.

[0034] After analysis, the server determines that the behavior data of user A does not hit the filtering rules and meets the conditions for pushing the recommended information of the available registration source to the user. Therefore, the server sends the recommended information of the available registration source corresponding to the target doctor information to the client through the instant message push service. The target doctor can be a doctor with no registration source that the user has visited, or other doctors similar to the doctor with no registration source.

[0035] User A receives the recommended information of available appointment sources on the client. For example, the client displays "The respiratory specialist of the tertiary hospital you are following has a new appointment available this afternoon. Click to make an appointment immediately." When user A clicks on the recommended information of available appointment sources, the client starts the registration interface and displays the registration entrance corresponding to the target doctor information. User A can directly make an appointment without repeated searches and successfully make an appointment with a doctor who can meet his needs.

[0036] In this scenario example, the client is a user application, and the user can receive and view the recommended information of available registration sources on the client. The server is responsible for collecting the user's medical-related behavior data, and based on this, generates a medical demand profile of the user. Based on the matching degree between the doctor information and the medical demand profile, combined with the real-time monitored number source information, the recommended information of available registration sources is pushed to the user. The specified filtering rules are used to analyze the user's historical behavior to ensure that the pushed recommendation information is accurate and effective. In this way, the registration platform can intelligently identify the user's medical needs, recommend the recommended information of available registration sources in real time, help users obtain the doctor's number sources that meet their needs as soon as possible, and improve the registration efficiency and user experience.

[0037] See also Figure 3 . The embodiment of the present application provides a number source recommendation method. The number source recommendation method can be applied to a number source recommendation device. The number source recommendation device can be an electronic device with certain computing capabilities and network access capabilities. Of course, the number source recommendation device can also refer to a software program running in an electronic device. In this embodiment, the number source recommendation method can include the following steps.

[0038] Step S110: Generate a medical needs portrait based on the medical-related behavior data generated by the user account; wherein the medical needs portrait is used to characterize the disease information of the user account.

[0039] Step S120: According to the medical needs portrait, matching doctor information matching the medical needs portrait is identified from a doctor information database; wherein the doctor represented by the matching doctor information is good at treating the disease represented by the disease information.

[0040] Step S130: monitor the appointment sources corresponding to the matching doctor information, and when the target doctor information screened out from the matching doctor information corresponds to an available appointment source, send the available appointment source recommendation information corresponding to the target doctor information to the user account.

[0041] In this embodiment, in order to recommend to users the available appointment sources that are suitable for their needs, the appointment source recommendation device can obtain the medical-related behavior data corresponding to the user account and generate a medical needs portrait, so that the medical needs portrait can represent the disease information (such as heart disease) of the user account. Among them, the medical-related behavior data is used to represent the behavior data corresponding to the online operations performed by the user to achieve the purpose of registration. The medical-related behavior data includes at least one of the following: medical-related interface access data, medical-related information search data, and historical medical-related operation data. Each data in the medical-related behavior data is stored in a structured form / unstructured form, and this embodiment of the application does not limit this. The medical needs portrait is the result of information extraction of medical-related behavior data. The medical needs portrait can concisely and accurately represent the disease information of the user account.

[0042] In this embodiment, the number source recommendation device can actively obtain the target doctor information that matches the user's medical needs based on the user's medical-related behavior data without the need for the user to perform a subscription operation, and actively monitor the number source situation, so that when the user is using the registration platform, it can actively send the user a recommendation information about the registration source. Furthermore, the number source recommendation device can further follow up on whether the user has obtained the registration information. In the case where it is determined that the user has obtained the registration information, it is considered that the user has completed the registration, and there is no need to further provide the recommendation information about the registration source. And when the user has generated medical-related behavior data and it is not detected that the user has obtained the registration information, the recommendation information about the registration source is sent to the user in accordance with the above scheme. In this way, the user can quickly and conveniently obtain a suitable registration source, which brings convenience to the user's medical treatment.

[0043] In this embodiment, the medical-related interface access data may include at least one of the following: hospital page access time, hospital page stay time, doctor page access time, doctor page stay time, corresponding number source when visiting the doctor page, whether the visited doctor page corresponds to the subscribed / followed doctor, hospital information corresponding to the visited department, and the number of clicks when visiting the department list. Medical-related information search data may include at least one of the following: historical search records of user accounts in the medical platform, and the stay time corresponding to the search results. Historical medical-related operation data may include historical registration orders.

[0044] In this embodiment, the medical-related interface access data, medical-related information search data, and historical medical-related operation data all correspond to the user account, and the user account may include a user ID, a payment account number, an ID number, etc. The comprehensive medical-related interface access data, medical-related information search data, and historical medical-related operation data can be matched to matching doctor information suitable for the user account, and the matching doctor information is selected from the doctor information database, and the matching doctor information may include but is not limited to: name, position, department, hospital, and disease that the doctor specializes in.

[0045] In this embodiment, the number source recommendation device can identify the matching doctor information that matches the medical demand portrait from the doctor information database. The matching doctor information indicates the disease that the doctor is good at treating, and the matching doctor information can include one or more doctor information. Specifically, the number source recommendation device can identify the similarity between each doctor information based on the similarity evaluation dimension; wherein the similarity evaluation dimension includes at least one of the following: good at disease information, department, region, and hospital; similarity is used as a basis for generating the matching degree. In order to match the matching doctor information that can meet the user's registration needs, the number source recommendation device can identify the similarity between each doctor information based on the good at disease information (such as good at liver cirrhosis), department (such as internal medicine), region (such as Shanghai), and hospital (such as Shanghai XX Hospital) in the similarity evaluation dimension, and then match the matching doctor information related to the medical demand portrait with the similarity between each doctor information. For example, the number source recommendation device can calculate the sub-similarity of each dimension in the similarity evaluation dimension for every two doctor information, obtain multiple sub-similarity, and fuse multiple self-similarity to obtain the corresponding similarity, based on which the similarity between each doctor information can be calculated. In addition, the similarity (e.g., 0.8) between at least one dimensional information in the target doctor's information (e.g., expertise in liver cirrhosis) and the corresponding dimensional information in the medical needs portrait (e.g., the presence of potential risk of liver cirrhosis) is greater than the preset similarity (e.g., 0.7).

[0046] In this embodiment, after obtaining the matching doctor information, the appointment source recommendation device can establish a corresponding relationship between the matching doctor information and the user account. In this way, the appointment source of the matching doctor information that has a corresponding relationship with the user account can be monitored to improve the speed of obtaining the target doctor information.

[0047] In this embodiment, the appointment source recommendation device can monitor the doctor information in the matching doctor information, and when the target doctor information corresponding to the available appointment source is monitored, the corresponding available appointment source recommendation information is generated based on the target doctor information and pushed to the client corresponding to the user account. Although the target doctor is not the doctor specified by the user, the target doctor is selected based on the user's medical-related behavior data, so the target doctor information matches the user's registration needs. When it is detected that the target doctor information corresponds to the available appointment source, the available appointment source recommendation information corresponding to the target doctor information can be pushed to the client for the user to make an appointment with the available appointment source corresponding to the available appointment source recommendation information. The user does not need to wait for the next appointment for the doctor who currently has no appointment, which saves the waiting time and can solve the problem of difficulty in online registration to a certain extent.

[0048] In this embodiment, the number source recommendation device can periodically detect the number source information in the real-time doctor number source collection system, and the number source information indicates the status of the available registration sources of each doctor. When it is detected that the target doctor information in the matching doctor information corresponds to the available registration source, it means that the doctor who can meet the user's registration needs has an appointment available. At this time, the available registration source recommendation information corresponding to the target doctor information can be pushed to the client corresponding to the user account. The available registration source recommendation information can be displayed in the client in the form of text messages, instant messaging messages in instant messaging software, voice messages, etc. The available registration source recommendation information is used to prompt the user that there is a doctor who meets his registration needs in the online medical platform and the doctor has an appointment available. The available registration source recommendation information includes but is not limited to the following information: target doctor information, recommendation words.

[0049] In this embodiment, after receiving the recommended information of the available registration source, the client can display the recommended information of the available registration source. When the user interface corresponding to the recommended information of the available registration source is detected to be triggered and started, the user interface can be displayed and the registration entrance corresponding to the target doctor information can be displayed in the user interface. The registration entrance can be a touch-sensitive control. When the registration entrance is detected to be triggered, it jumps to the registration interface corresponding to the target doctor, and the registration interface is used to provide an appointment registration service for the target doctor. Among them, the user interface corresponding to the recommended information of the available registration source can be the main page of the online medical platform, the sub-interface corresponding to the registration function, etc., and this embodiment of the application does not limit this.

[0050] The appointment recommendation method provided in the implementation mode of the present application generates a corresponding medical need portrait based on the medical-related behavior data of the user account. Since the medical need portrait can represent the disease information of the user account, the matching doctor information can be identified based on the medical need portrait. The doctor represented by the matching doctor information is good at treating the disease represented by the disease information. Furthermore, when it is monitored that the target doctor information in the matching doctor information corresponds to an available appointment source, the corresponding available appointment source recommendation information can be recommended to the user account, so as to reduce the waiting time for the appointment source and help the user's appointment needs to be met in a timely manner.

[0051] In some embodiments, the number recommendation device can perform structured processing on the medical-related behavior data to obtain structured medical data corresponding to the user account; and construct prompt instructions based on the structured medical data of the user account to instruct the called large language model to generate a medical demand portrait of the user account.

[0052] In this embodiment, in order to improve the matching degree between the recommended number source and the user's needs, the number source recommendation device can structure the medical-related behavior data into structured medical data, and input prompt instructions containing the medical demand portrait dimension and structured medical data to the large language model to instruct the large language model to refine the structured medical data into a medical demand portrait. Among them, the medical demand portrait dimension indicates the fields that need to be included in the medical demand portrait, such as name, disease information, medical history, etc. Among them, the medical-related behavior data is unstructured data, and the structured medical data includes multiple fields and field values. The multiple fields may include but are not limited to: user name, gender, age, disease information, etc.

[0053] In some embodiments, the medical needs portrait includes at least one of the following dimensional information: potential health problems, preferred departments, preferred hospitals, and preferred doctors.

[0054] In this embodiment, in order to improve the matching degree between the medical demand portrait and the user account, and to further improve the matching degree between the matching doctor information selected based on the medical demand portrait and the user account, the dimensional information contained in the medical demand portrait can be limited. Among them, potential health problems refer to one or more health risks that may exist in the user account obtained by analyzing the medical-related behavior data. The preferred department refers to the department that the user account has visited many times according to the analysis of the medical-related behavior data. The preferred hospital refers to the hospital platform that the user account has visited many times according to the analysis of the medical-related behavior data. The preferred doctor refers to the doctor information that the user account has visited many times according to the analysis of the medical-related behavior data. Based on the dimensional information such as potential health problems, preferred departments, preferred hospitals, and preferred doctors (such as Dr. Wang), matching doctor information with correlation with the medical demand portrait can be matched, and at least one of the disease information, department, region, and hospital contained in the matching doctor information can be matched with the medical demand portrait.

[0055] In some embodiments, the appointment recommendation device can periodically obtain doctor data from multiple medical institutions; wherein the doctor data includes doctor profile information for introducing the doctor's resume; construct prompt instructions based on the doctor profile information to call a large language model to generate the doctor's specialty disease data; after structuring the specialty disease data, store it to obtain a doctor information database; wherein the doctor information database correspondingly stores the doctor's identification and structured specialty disease data.

[0056] In this embodiment, in order to improve the efficiency of obtaining matching doctor information, a doctor information database can be constructed before determining the matching doctor information. The doctor information in the doctor information database can come from the doctor data of multiple medical institutions, and the number source recommendation device can obtain the corresponding doctor data by calling the corresponding interfaces of multiple medical institutions. Since the doctor information includes the doctor profile information, the large language model can be triggered to use the prompt instruction to extract the disease data in the doctor profile information, and the disease data can be stored as the doctor information after structured processing. The prompt instruction can be used to define the information extraction rules for the doctor profile information.

[0057] In this embodiment, the number source recommendation device can also periodically obtain incremental doctor data from multiple medical institutions. The incremental doctor data includes but is not limited to the supplementary information of the original doctors and the information of the newly added doctors. Then, the large language model can be called to generate the disease data of the incremental doctor data, and the data is structured and stored as doctor information in the doctor information database. After obtaining the incremental doctor data from the hospital system, the number source recommendation device can also detect the data cleaning operation. When the data cleaning operation is detected, the incremental doctor data is updated based on the data cleaning operation to ensure the data accuracy of the incremental doctor data. The data cleaning operation can include operations such as adding, deleting, and modifying the incremental doctor data.

[0058] In some embodiments, the number source recommendation device can filter the matching doctor information according to specified filtering rules based on the medical-related behavior data of the user account to obtain the target doctor information; wherein the specified filtering rules include: the doctor interface has been visited, the visited doctor interface has no number source, no number has been registered for a department similar to the visited doctor interface without a number source within a first preset time period, and the number of visits to the doctor interface without a number source within a second preset time period meets a preset number of times.

[0059] In this embodiment, in order to more accurately recommend a number source to the user, invalid recommendations are avoided. The number source recommendation device can identify matching doctor information that matches the medical-related behavior data from the doctor information database, and when it is detected that the target doctor information in the matching doctor information corresponds to a source that can be registered, analyze the medical-related behavior data based on the specified filtering rules to obtain the analysis result. In some cases, invalid recommendations are prone to occur. For example, if the medical-related behavior data indicates that the doctor visited by the user has no number available, but the user has not made a registration query for a period of time, it means that the user may have gone to register offline or has no registration needs. Therefore, the number source recommendation device is set with a specified filtering rule, and the specified filtering rule is used to limit one or more rules that do not need to be recommended. If the medical-related behavior data hits the conditions in the specified filtering rule, the number source recommendation is not made to the user account. In the case where the analysis result indicates that the medical-related behavior data does not hit the specified filtering rule, the available registration source recommendation information corresponding to the target doctor information is pushed to the client.

[0060] In some embodiments, the specified filtering rules include: the doctor interface has been visited, the doctor interface has no number source, the number of departments similar to the doctor interface without number source that has been visited has not been registered within the first preset time length, and the number of visits to the doctor interface without number source within the second preset time length meets the preset number of times. In order to achieve effective recommendation of number sources, the number source recommendation device limits the specific content of the specified filtering rules. In one embodiment, the medical-related behavior data can be analyzed in sequence according to the following conditions: the doctor interface has been visited, the doctor interface has no number source, the number of departments similar to the doctor interface without number source that has been visited has not been registered within the first preset time length (such as 7 days), and the number of visits to the doctor interface without number source within the second preset time length (such as 15 days) meets the preset number of times, in that order. In the case that the medical-related behavior data hits any of the above, the number source recommendation is canceled. In the case that the medical-related behavior data does not hit any of the above, the recommended number source corresponding to the target doctor information is pushed to the client corresponding to the user account.

[0061] See also Figure 4 . An embodiment of the present application provides a method for displaying number source recommendation information. The method for displaying number source recommendation information can be applied to a number source recommendation information display device. The number source recommendation information display device can be an electronic device with certain computing capabilities and network access capabilities. Of course, the number source recommendation information display device can also refer to a software program running in an electronic device. In this embodiment, the method for displaying number source recommendation information can include the following steps.

[0062] Step S210: receiving the available appointment source recommendation information corresponding to the target doctor information sent by the appointment source recommendation method.

[0063] Step S220: Display the recommended information of the available appointment sources.

[0064] In this embodiment, the method for displaying the recommended appointment source information is applied to the client; the recommended appointment source information display device can display the recommended appointment source information on the homepage of the client; when the display area corresponding to the recommended appointment source information is triggered, the registration entrance corresponding to the target doctor information is displayed.

[0065] In this embodiment, the specific functions and effects achieved by the number source recommendation information display method can be explained with reference to other embodiments of the present application and will not be repeated here.

[0066] See also Figure 5. One embodiment of the present application also provides a device for recommending a number source. The device for recommending a number source may include: a medical need portrait generation module, which is used to generate a medical need portrait based on the medical-related behavior data generated by the user account; wherein the medical need portrait is used to characterize the disease information of the user account; a doctor information matching module, which is used to identify matching doctor information that matches the medical need portrait from a doctor information database based on the medical need portrait; wherein the doctor represented by the matching doctor information is good at treating the disease represented by the disease information; a number source recommendation module, which is used to monitor the number source corresponding to the matching doctor information, and when the target doctor information screened out from the matching doctor information corresponds to a registrable source, send the registrable source recommendation information corresponding to the target doctor information to the user account.

[0067] In this embodiment, the specific functions and effects achieved by the number source recommendation device can be explained with reference to other embodiments of the present application and will not be repeated here.

[0068] See also Figure 6 One embodiment of the present application further provides a device for displaying information on recommended appointment sources. The device for displaying information on recommended appointment sources may include: an information receiving module for receiving the recommended appointment source information corresponding to the target doctor information sent by the device for recommending appointment sources; and an information display module for displaying the recommended appointment source information.

[0069] In this embodiment, the specific functions and effects achieved by the number source recommendation information display device can be explained with reference to other embodiments of the present application and will not be repeated here.

[0070] The embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the processor implements the aforementioned number source recommendation method or number source recommendation information display method.

[0071] The embodiment of the present application also provides a computer program product comprising instructions, which, when executed by a processor, implements the aforementioned number source recommendation method or number source recommendation information display method.

[0072] See also Figure 7 . The implementation method of this description can provide a computer device, which includes: a memory, and one or more processors communicatively connected to the memory; the memory stores instructions that can be executed by the one or more processors, and the instructions are executed by the one or more processors to enable the one or more processors to implement the aforementioned number source recommendation method or number source recommendation information display method.

[0073] In some embodiments, the computer device may include a processor, a non-volatile storage medium, an internal memory, a communication interface, a display device, and an input device connected by a system bus. The non-volatile storage medium may store an operating system and related computer programs.

[0074] The user information or user account information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, etc.) involved in multiple implementation methods of the present application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws and standards of relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0075] It should be understood that the specific examples in this article are only intended to help those skilled in the art to better understand the embodiments of the present application, rather than to limit the scope of the present invention.

[0076] It can be understood that in the various implementations of the present application, the size of the serial number of each process does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the implementation methods of the present application.

[0077] It can be understood that the various embodiments described in this application can be implemented individually or in combination, and the embodiments of this application are not limited to this.

[0078] Unless otherwise stated, all technical and scientific terms used in the embodiments of the present application have the same meaning as those generally understood by those skilled in the art of the technical field of the present application. The terms used in the present application are only for the purpose of describing specific embodiments and are not intended to limit the scope of the present application. The term "and / or" used in the present application includes any and all combinations of one or more related listed items. The singular forms of "a kind of", "above" and "the" used in the embodiments of the present application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings.

[0079] It can be understood that the processor of the embodiment of the present application can be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method implementation can be completed by the hardware integrated logic circuit or software instructions in the processor. The above processor can be a general processor, a digital signal processor (DigitalSignal Processor, DSP), an application-specific integrated circuit (Application Specific Integrated Circuit, ASIC), a field programmable gate array (Field Programmable Gate Array, FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiment of the present application can be implemented or executed. The general processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in the embodiment of the present application can be directly embodied as a hardware decoding processor to perform, or the hardware and software modules in the decoding processor are combined and executed. The software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.

[0080] It is understood that the memory in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memory. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (programmable ROM, PROM), an erasable programmable read-only memory (erasable PROM, EPROM), an electrically erasable programmable read-only memory (EEPROM) or a flash memory. The volatile memory may be a random access memory (RAM). It should be noted that the memory of the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0081] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0082] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method implementation methods and will not be repeated here.

[0083] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device implementation described above is only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0084] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0085] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0086] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0087] The above is only a specific implementation of the present application, but the protection scope of the present invention is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for recommending a number source, characterized in that: include: Generate a medical demand portrait based on the medical-related behavior data generated by the user account; wherein the medical demand portrait is used to characterize the disease information of the user account; According to the medical demand portrait, matching doctor information matching the medical demand portrait is identified from a doctor information database; wherein the doctor represented by the matching doctor information is good at treating the disease represented by the disease information; The appointment source corresponding to the matching doctor information is monitored, and when the target doctor information screened out from the matching doctor information corresponds to an available appointment source, the available appointment source recommendation information corresponding to the target doctor information is sent to the user account.

2. The method according to claim 1, characterized in that: The steps for generating a medical demand profile based on the medical-related behavior data generated by the user account include: Performing structured processing on the medical-related behavior data to obtain structured medical data corresponding to the user account; A prompt instruction is constructed according to the structured medical data of the user account to instruct the invoked large language model to generate a medical needs portrait of the user account.

3. The method according to claim 2, characterized in that The medical needs portrait includes at least one of the following dimensional information: potential health problems, preferred departments, preferred hospitals, and preferred doctors.

4. The method according to claim 1, characterized in that: The method further comprises: Periodically obtaining doctor data from multiple medical institutions; wherein the doctor data includes doctor profile information for introducing the doctor's resume; Constructing prompt instructions according to the doctor's profile information to call the large language model to generate the doctor's specialty disease data; After the disease data are structured, a doctor information database is stored; wherein the doctor information database stores the doctor identification and structured disease data.

5. The method according to claim 1, characterized in that: The step of monitoring the appointment source corresponding to the matching doctor information, and sending the available appointment source recommendation information corresponding to the target doctor information to the user account when the target doctor information screened out from the matching doctor information corresponds to the available appointment source, comprises: Based on the medical-related behavior data of the user account, the matching doctor information is filtered according to the specified filtering rules to obtain the target doctor information; wherein the specified filtering rules include: the doctor interface has been visited, the visited doctor interface has no number source, no number of departments similar to the visited doctor interface without a number source has been registered within a first preset time period, and the number of visits to the doctor interface without a number source within a second preset time period meets the preset number of times.

6. A method for displaying number source recommendation information, characterized in that: include: Receiving the available appointment source recommendation information corresponding to the target doctor information sent by the appointment source recommendation method as described in any one of claims 1 to 5; The recommended information of the available registration sources is displayed.

7. The method according to claim 6, characterized in that The method for displaying number source recommendation information is applied to a client; the method further comprises: Displaying the recommended information of the available appointment sources on the homepage of the client; When the display area corresponding to the recommended information of the available registration source is triggered, the registration entrance corresponding to the target doctor information is displayed.

8. A signal source recommendation device, characterized in that: include: A medical needs portrait generation module, used to generate a medical needs portrait based on the medical-related behavior data generated by the user account; wherein the medical needs portrait is used to characterize the disease information of the user account; A doctor information matching module, used to identify matching doctor information matching the medical demand portrait from a doctor information database according to the medical demand portrait; wherein the doctor represented by the matching doctor information is good at treating the disease represented by the disease information; The appointment source recommendation module is used to monitor the appointment source corresponding to the matching doctor information, and when the target doctor information screened out from the matching doctor information corresponds to an available appointment source, send the available appointment source recommendation information corresponding to the target doctor information to the user account.

9. A device for displaying number source recommendation information, characterized in that: include: An information receiving module, used for receiving the available appointment source recommendation information corresponding to the target doctor information sent by the appointment source recommendation device as claimed in claim 8; The information display module is used to display the recommended information of the available appointment sources.

10. A computer device, characterized in that: The computer device includes a memory and a processor, wherein the memory stores at least one computer program, and the at least one computer program is loaded and executed by the processor to implement the number source recommendation method according to any one of claims 1 to 5 or the number source recommendation information display method according to any one of claims 6 to 7.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores at least one computer program, and when the at least one computer program is executed by the processor, it can implement the number source recommendation method according to any one of claims 1 to 5 or the number source recommendation information display method according to any one of claims 6 to 7.

12. A computer program product, characterized in that The computer program product is used to implement the number source recommendation method according to any one of claims 1 to 5 or the number source recommendation information display method according to any one of claims 6 to 7.

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